Linear and Nonlinear Non-minimal State Space Control System Design

This tutorial chapter uses case studies based on recent engineering applications, to re-examine the non-minimal, state variable feedback approach to control system design. We show how the non-minimal state space (NMSS) representation seems to be the natural description of a discrete-time Transfer Function, since its dimension is dictated by the complete structure of the model. This is in contrast to minimal state space descriptions, which only account for the order of the denominator and whose state variables, therefore, usually represent combinations of input and output signals. The resulting control algorithm can be interpreted as a logical extension of the conventional Proportional-Integral (PI) controller, facilitating its straightforward implementation using a standard hardware-software arrangement. Finally, the basic NMSS approach is readily extended into multivariable, model-predictive and nonlinear control systems, hence the chapter briefly discusses these areas and gives pointers to the latest research results.

[1]  Peter C. Young,et al.  Modelling and proportional-integral-plus control design for free air carbon dioxide enrichment systems , 2000 .

[2]  M. A. Stables,et al.  Proportional-integral-plus control applications of state-dependent parameter models , 2007 .

[3]  P. Young,et al.  An improved structure for model predictive control using non-minimal state space realisation , 2006 .

[4]  Peter C. Young,et al.  Non-minimal state-space model-based continuous-time model predictive control with constraints , 2009, Int. J. Control.

[5]  Jun Gu,et al.  Proportional‐Integral‐Plus Control of an Intelligent Excavator , 2004 .

[6]  Darci Odloak,et al.  Infinite horizon MPC with non-minimal state space feedback , 2009 .

[7]  A. Callender,et al.  Time-Lag in a Control System , 1936 .

[8]  Vasileios Exadaktylos,et al.  Multi-objective performance optimisation for model predictive control by goal attainment , 2010, Int. J. Control.

[9]  Keith J. Burnham,et al.  Controllable forms for stabilising pole assignment design of generalised bilinear systems , 2011 .

[10]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[11]  E. M. Shaban,et al.  Development of an automated verticality alignment system for a vibro-lance , 2008 .

[12]  Diego J. Pedregal,et al.  Environmental time series analysis and forecasting with the Captain toolbox , 2007, Environ. Model. Softw..

[13]  Peter C. Young,et al.  Direct digital and adaptive control by input-output state variable feedback pole assignment , 1987 .

[14]  Peter C. Young,et al.  Modelling and PIP control of a glasshouse micro-climate , 1994 .

[15]  Peter C. Young,et al.  Non-linear control by input–output state variable feedback pole assignment , 2009, Int. J. Control.

[16]  Peter C. Young,et al.  PIP optimal control with a risk sensitive criterion , 1996 .

[17]  H. T. Banks,et al.  Nonlinear feedback controllers and compensators: a state-dependent Riccati equation approach , 2007, Comput. Optim. Appl..

[18]  C. James Taylor,et al.  Nonlinear control system design for construction robots using state dependent parameter models. , 2006 .

[19]  E. M. Shaban,et al.  Multivariable proportional-integral-plus (PIP) control of the ALSTOM nonlinear gasifier simulation , 2006 .

[20]  Daniel Berckmans,et al.  Cost effective combined axial fan and throttling valve control of ventilation rate , 2004 .

[21]  Peter C. Young,et al.  Nonlinear and Nonstationary Signal Processing , 1998, Technometrics.

[22]  P. Young,et al.  State space control system design based on non-minimal state-variable feedback: Further generalization and unification results , 2000 .

[23]  P. Young,et al.  Proportional-integral-plus (PIP) design for delta (delta) operator systems Part 2. MIMO systems , 1998 .

[24]  Peter C. Young,et al.  Recursive Estimation and Time Series Analysis , 1984 .

[25]  Naresh K. Sinha,et al.  Modern Control Systems , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[26]  Benjamin C. Kuo,et al.  Digital Control Systems , 1977 .

[27]  D. Luenberger Observing the State of a Linear System , 1964, IEEE Transactions on Military Electronics.

[28]  R.J.D. Reeves Feedback-amplifier design , 1952 .

[29]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[30]  C. James Taylor,et al.  State dependent control of a robotic manipulator used for nuclear decommissioning activities , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[31]  P. Young,et al.  An approach to the linear multivariable servomechanism problem. , 1972 .

[32]  Peter C. Young,et al.  Continuous-time non-minimal state-space design , 2007, Int. J. Control.

[33]  Peter C. Young,et al.  Nonminimal state space approach to multivariable ramp metering control of motorway bottlenecks , 1998 .